title: A quantitative analysis of F-actin features and distribution in fluorescence microscopy images to distinguish cells with different modes of motility.
abstract: Actin is one of the most abundant proteins in eukaryote cells, playing a key role in cell dynamic morphological alterations and tumor metastatic spread. To investigate the relationship between the distribution patterns of actin and the aggressiveness of cancer cells, we developed an image analysis framework for quantifying cell F-actin distributions examined with fluorescence microscopy. The images are first segmented with multichannel information of both F-actin and nuclear staining. Using the watershed method and Voronoi tessellation, the cells can be well segmented based on both F-actin and nuclear information. Altogether, sixteen F-actin distribution features are calculated for each individual cell. A linear Support Vector Machine (SVM) is then applied in the feature space to separate cells with different modes of motility. Our results show that cells with different modes of motility can be distinguished by F-actin distributions. To our knowledge, this is the first study managing to distinguish cancer cells with different aggressiveness based on quantitative analysis of F-actin distribution patterns.
authors.forename: Jie
authors.initials: J
authors.lastname: Cheng
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Zhu
authors.forename: Hao
authors.initials: H
authors.lastname: Cheng
authors.forename: Hong
authors.initials: H
authors.lastname: Zhao
authors.forename: Stephen T C
authors.initials: ST
authors.lastname: Wong
mesh_terms: D000199:Actins / Q000378:metabolism*; D002460:Cell Line; D002465:Cell Movement; D004847:Epithelial Cells / Q000166:cytology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008856:Microscopy, Fluorescence / Q000379:methods*; D060388:Support Vector Machine
chemical_list: D000199:Actins